Table 1 Top contributing factors affecting motorcycle involved crashes.

Rider demographic

Rider age

(Farid and Ksaibati, 2021; Pour-Rouholamin et al., 2017; Seyfi et al., 2023)

Motorcyclists’ behavior

Excessive entry speed, combined with inattention and poor cornering skills, helmet use, alcohol use

(Brockhus et al., 2024; Eustace et al., 2011; Pour-Rouholamin et al., 2017; Rangaswamy et al., 2022; Wang et al., 2014)

Curve features

Curve radius

(Gabauer and Li, 2015; Wang et al., 2014; Xin et al., 2017)

Horizontal curves

(Farid and Ksaibati, 2021; Kvasnes et al., 2021; Rangaswamy et al., 2022; Z. Wang et al., 2019; Xin et al., 2017; Alnawmasi and Mannering, 2019)

Reverse curves

(Kvasnes et al., 2021; Xin et al., 2017)

Sharp non reverse curve

(Xin et al., 2019, 2018)

Wider lanes and shoulder

(Kvasnes et al., 2021)

Lean angle

(Rose et al., 2018; Wahba et al., 2019)

Manner of collision

Single motorcycle crash

(Farid and Ksaibati, 2021; Kvasnes et al., 2021; Wang et al., 2014; Xin et al., 2017, 2018, 2019)

Multiple vehicle crashes

(Farid and Ksaibati, 2021)

Collision with fixed objects (e.g., trees, utility poles)

(Ding et al., 2019; Wang et al., 2014)

Head on collision

(Ding et al., 2019)

Rider ejection

(Das et al., 2018)

Roadway characteristics

Wet surface

(Pour-Rouholamin et al., 2017)

Rural two-lane curves

(Das et al., 2018; Rangaswamy et al., 2022; Xin et al., 2019)

Environmental condition

Adverse weather, lighting conditions (dark)

(Pour-Rouholamin et al., 2017; Wang et al., 2014)

Temporal factors

Weekend, winter, and summer season

(Das et al., 2018; Pour-Rouholamin et al., 2017)

Other factors

Motorcycle Curve Assist (MCA), flashing beacons, signage and marking

(Brumec et al., 2019; Lucci et al., 2022; Rangaswamy et al., 2022)